Abstract
One of the core assumptions made when building agent-based simulation models is how the agents decide or reason about the action to take next. The mode of reasoning is usually the same for all agents and over time within the simulation run. However, is this adequate? There exist several frameworks that describe multi-mode reasoning, however how do we know what we need? To engage with this core question, we reflect on this modelling process, by using CAFCA—one of these multi-mode frameworks—and reflect on the reasoning dimension in a social dilemma decision situation. More specifically, using existing qualitative inquiry on group dynamics in a common pool resource dilemma—not designed to elicit different types of reasoning—we introduce our hunt for reasoning hints and reflect on what insights/data we would need to make an informed decision about the reasoning(s) in our modelling and how to obtain this.
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References
Carley, K., Newell, A.: The nature of the social agent. J. Math. Soc. 19(4), 221–262 (1994)
Elsenbroich, C., Verhagen, H.: The simplicity of complex agents: a contextual action framework for computational agents. Mind Soc. 15(1), 131–143 (2016)
Jansen, M., Jager, W.: An integrated approach to simulating behavioural processes: a case study of the lock-in of consumption patterns. J. Artif. Soc. Soc. Simul. 2(2) (2000)
Kahneman, D.: Thinking, Fast and Slow. Farrar, Straus & Giroux (2011)
Kollock, P.: Social dilemmas: the anatomy of cooperation. Ann. Rev. Soc. 24(1), 183–214 (1998)
Lindahl, T., Schill, C., Jarungrattanapong, R.: Beijer discussion paper 276: the role of resource dependency for sharing increasingly scarce resources: evidence from a behavioural experiment with small-scale fishers. In: Beijer Discussion Paper Series (2021)
Simon, H.A.: A behavioural model of rational choice. Q. J. Econ. 69(1), 99–118 (1955)
Wijermans, N., Schill, C., Lindahl, T., Schlüter, M.: AgentEx (2016). https://doi.org/10.25937/js95-6d78
Wijermans, N., Schill, C., Lindahl, T., Schlüter, M.: Combining approaches: looking behind the scenes of integrating multiple types of evidence from controlled behavioural experiments through agent-based modelling. Int. J. Soc. Res. Methodol. 4, 1–13 (2022). https://doi.org/10.1080/13645579.2022.2050120
Wijermans, N., Verhagen, H.: Fishing together? - exploring the murky waters of sociality. In: Dam, K.H.V., Verstaevel, N. (Eds.). Multi-Agent-Based Simulation XXII - 22nd International Workshop, MABS 2021, Virtual Event, May 3-7, 2021, Revised Selected Papers. Lecture Notes in Computer Science, vol. 13128, pp. 180–193. Springer (2021). https://doi.org/10.1007/978-3-030-94548-0_14, https://doi.org/10.1007/978-3-030-94548-0_14
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Wijermans, N., Verhagen, H. (2023). Formalising Agent Reasoning—The Paso Doble of Data and Theory. In: Squazzoni, F. (eds) Advances in Social Simulation. ESSA 2022. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-031-34920-1_42
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DOI: https://doi.org/10.1007/978-3-031-34920-1_42
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